Data Science Manager

Ubiety is the creator of HomeAware, an AI-powered mobile application that delivers real-time presence insights during alarm events and beyond, so you always know who’s home when it matters most. Our platform provides meaningful, contextual notifications that prioritize awareness over reaction, helping families feel safer without the burden of unnecessary emergency calls or intrusive surveillance.

With the introduction of HomeAware, Ubiety is redefining the home security experience. By combining cutting-edge AI with seamless smart home integration, we ensure our users are better informed, more in control, and able to protect what matters most.

We’re looking for a Data Science Manager to help scale Ubiety’s HomeAware product and data function across a rapidly expanding set of commercial customers and public-sector use cases. Reporting directly to the CTO, this role will both deliver hands-on machine learning solutions and guide our team of data scientists as we build production-grade systems. This role is centered on real-world product impact: shipping models, improving performance in live environments, partnering with engineering and product, and ensuring our AI delivers consistent value to users.

As a Data Science Manager at Ubiety, you'll get to:

• Build and own the end-to-end lifecycle of ML models powering HomeAware, from data ingestion to deployment and monitoring.

• Build, train, evaluate, deploy, and iterate on ML models for classification, regression, and detection problems.

• Partner with Engineering to productionize models, move code out of notebooks, and integrate into backend services.

• Improve model performance in real-world conditions through validation, experimentation, and feedback loops.

• Help define Ubiety’s data science roadmap with a focus on product outcomes and delivery.

• Drive a data-driven culture by connecting metrics, models, and decisions to business impact.

• Work closely with Product, Engineering, and UX to translate product needs into ML solutions.

• Communicate model behavior, tradeoffs, and performance clearly to technical and non-technical stakeholders.

The ideal candidate will have:

• Strong Python programming experience using pandas, numpy, scipy, scikit-learn, keras/pytorch, h2o.

• Strong product intuition and comfort operating in ambiguous, fast-moving environments.

• Extensive experience pulling data from SQL and NoSQL databases (e.g., Snowflake, Postgres, Cassandra, Redis).

• Experience applying software engineering best practices to production ML (modularity, testing, CI/CD, version control).

• Proven experience developing and shipping ML models for classification and regression problems.

• Experience building visualizations and presentations for non-technical audiences.

• Familiarity with AWS services and cloud-based workflows.

What we can offer you:

• True ownership and autonomy. This is a role for someone who wants to take ideas from concept to execution to impact. You’ll have the freedom and responsibility to build, test, and scale what works.

• A highly collaborative, transparent culture. We operate with openness, trust, and direct communication. You’ll have visibility into decisions, context behind priorities, and access to the people driving them.

• A results-driven, learning-oriented environment. We care deeply about outcomes, but we also value thoughtful experimentation, fast feedback loops, and continuous improvement.

• Equity ownership in a fast-growing company. You’ll share in the upside of what we’re building together.

• Competitive, people-first benefits.

  • Subsidized healthcare coverage

  • Hybrid Working Schedule three days in HQ office (River North)

  • Unlimited PTO. We trust you to deliver results, then take real time to disconnect and recharge

• A team that has each other’s backs. We’re a small, tight-knit group that genuinely cares about doing great work and leveling up together along the way.